[unreadable] We propose to apply a novel systems biology technology for elucidation of human functional pathways implicated in breast cancer. We will analyze publicly available disease's microarray gene expression data in our data mining suit MetaCore and reconstruct signaling, regulatory and metabolic networks specifically affected in the disease. MetaCore consists of a comprehensive database of human pathways and protein interactions from experimental literature, visualization and network reconstruction tools. Using multiple network building and comparison algorithms, we will elucidate the network modules that are either associated with specific tumor subtypes (for example, associated with estrogen receptor status, mutations in BRCA1, BRCA2 and other genes) or could be predictive of treatment response and metastasis prognosis. We call these characteristic modules "signature networks". Unlike "molecular signatures" - lists of unconnected genes identified by clustering of microarray data points, such networks reflect and reveal the disease mechanisms. Conditional "signature networks" will be used as a novel type of diagnostics and a source for novel drug targets for breast cancer. [unreadable] [unreadable] [unreadable]